Scientific Publications in the Field of Agricultural Economics: Scientometric Analysis of Topics

Abstract

The relevance of the study is related to the need to assess the level of development of scientific knowledge and the degree of development of individual scientific problems in the field of agricultural economics. The purpose of this work is to study the dynamics of the number of publications in the field of agricultural economics in Russia and highlight their main topics. The main research method is content analysis within the bibliometric research. The results indicate great attention of scientists to various aspects of agricultural economics. However, from 2019 to 2023, the number of publications devoted to agricultural economics decreases. During the period under review, researchers pay the greatest attention to the following topics: “Accounting and analysis of economic activities”, “Financing and lending. Investments”. As the content analysis has shown, a significant number of publications are devoted to the problems of ensuring food security and sustainable development; innovative technologies, including digital ones; development of rural areas; issues related to government support and government regulation, productivity, competitiveness, small business, organic agriculture, investment, efficiency and agricultural management. At the same time, there is a relatively small number of publications devoted to pricing and labor resources, despite the relevance of these topics. In some years, there is a sharp increase in the number of publications on some topics. Thus, in 2019, the attention of researchers was as attracted by the topic of accounts payable and receivable, in 2020–2022 – programs for the development and support of agriculture, in 2020 and in 2023 – automation, in 2022 – import substitution. In 2021, there began to appear publications on the pandemic and unmanned technologies, and in 2023 – on artificial intelligence. Based on the calculation of the TF-IDF measure, it is concluded that there is greater similarity between the topics of publications in adjacent years than in non-adjacent ones. The results obtained can be used to plan the topics of research work.